Posted in | News | Green Energy

Highly Efficient and Stable OER Catalyst Developed for Acidic Water Splitting

A recent study published in Angewandte Chemie International Edition by researchers at Tohoku University identifies Ru3Zn0.85W0.15Ox (RZW), a ternary oxide catalyst, as a potential solution to the challenge of achieving high catalytic activity and durability in acidic environments.

Analysis of the crystal and electronic structures after the OER process. Image Credit: Hao Li et al.

The newly developed catalyst significantly enhances the stability and efficiency of the oxygen evolution reaction (OER) in acidic media.

OER is a key reaction in water splitting and is essential for producing green hydrogen, a potential sustainable and carbon-free energy source. However, conventional catalysts often struggle to maintain high performance and stability in acidic environments.

The study identifies RZW as a novel catalyst that improves OER performance by leveraging the electron-withdrawing properties of tungsten (W) and the sacrificial behavior of zinc (Zn).

According to the findings, zinc dissolves from the catalyst during the initial OER process, releasing electrons that are subsequently absorbed by tungsten species. This electron accumulation enhances catalytic activity by modifying the electronic environment of the ruthenium (Ru) sites.

Additionally, tungsten plays a stabilizing role by preferentially occupying bridge sites, preserving the active Ru configurations and maintaining the catalyst’s structural integrity and efficiency even after zinc dissolution.

The research team analyzed the catalyst's structural and electronic properties under OER conditions using a combination of theoretical density functional theory (DFT) calculations and advanced experimental techniques, including Fourier-transform extended X-ray absorption fine structure (FT-EXAFS), high-resolution transmission electron microscopy (HRTEM), and X-ray photoelectron spectroscopy (XPS).

The results indicate that zinc's rapid dissolution enhances electron transfer, improving both the catalyst's OER activity and long-term stability.

This breakthrough demonstrates how strategic doping with tungsten and the use of sacrificial metals like zinc can greatly improve the performance of OER catalysts. Our findings suggest that this approach offers a promising pathway for developing high-performance, cost-effective catalysts for green hydrogen production, which is crucial in the transition to renewable energy.

Hao Li, Associate Professor and Study Corresponding Author, Advanced Institute for Materials Research, Tohoku University

The research has been made accessible through the Hao Li Lab's Digital Catalysis Platform (DigCat), the largest experimental catalysis database to date.

The study was supported by the Tohoku University Support Program, which provided funding for the article processing charge (APC).

Next, the RZW catalyst will be tested in full electrolyzer systems to assess its performance in practical applications. The research team aims to contribute to the development of more efficient and scalable hydrogen production technologies by bridging the gap between fundamental research and real-world implementation.

Photoelectrochemical (PEC) Water Splitting for Hydrogen Production

Journal Reference:

Li, C., et al. (2025) W‐mediated electron accumulation in Ru‐O‐W motifs enables ultra‐stable oxygen evolution reaction in acid. Angewandte Chemie International Edition. doi.org/10.1002/anie.202422707.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.